HEMLab is a research team based within the School of Architecture, Building and Civil Engineering at Loughborough University, specialising in the development of high-performance modelling and data analytics tools to support natural hazard risk assessment and management. HEMLab also includes members from the Key Laboratory of Coastal Disaster and Defence at Hohai University (China).
Working at the forefront of computational and data technologies, we develop new numerical methods and models for simulating flooding and the associated transport processes, including sediment dynamics, hydro-geomorphological change, floating debris and pollutant transport, using the latest high-performance computing technology based on graphics processing units (GPUs).
The high-performance numerical methods and models are adapted and applied to simulate other types of natural hazards, including dam-break floods, tsunamis, storm surges, flow-like landslides and debris flows.
We explore and use the latest deep machine learning algorithms to enhance model capability for flood modelling and real-time forecasting.
We couple these high-performance models with data analytics and informatics tools to generate new methodology for Natural Hazards Assessment.
We develop and apply innovative modelling and digital tools to support sustainable flood risk management through working with natural processes.
Geomorphological change during a flood event.